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Prediction of Interpolants in Subsampled Radargram Slices

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Prediction of Interpolants in Subsampled Radargram Slices


T. Kishan Rao | E. G. Rajan | Dr. M Shankar Lingam



T. Kishan Rao | E. G. Rajan | Dr. M Shankar Lingam "Prediction of Interpolants in Subsampled Radargram Slices" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1, December 2020, pp.1402-1414, URL: https://www.ijtsrd.com/papers/ijtsrd38207.pdf

This paper provides an algorithmic procedure to predict interpolants of subsampled images. Given a digital image, one can subsample it by forcing pixel values in the alternate columns and rows to zero. Thus, the size of the subsampled image is reduced to half of the size of the original image. This means 75% of the information in the original image is lost in the subsampled image. The question that arises here is whether it is possible to predict these lost pixel values, which are called interpolants so that the reconstructed image is in accordance with the original image. In this paper, two novel interpolant prediction techniques, which are reliable and computationally efficient, are discussed. They are (i) interpolant prediction using neighborhood pixel value averaging and (ii) interpolant prediction using extended morphological filtering.

Ground Penetrating Radar, Subsurface Imaging, Targeted Buried Object Detection, Interpolant Prediction


IJTSRD38207
Volume-5 | Issue-1, December 2020
1402-1414
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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